Integrated SWAT model and Statistical Downscaling for Estimating Streamflow Response to Climate Change in the Lake Dianchi Watershed, China

Jing Zhou, Dan He,Yufeng Xie, Yong Liu, Huaicheng Guo, Yonghui Yang, Hu Sheng, Lei Zhao, Zou Rui

Abstract: Understanding the relationships between hydrological regime and climate change is important for water resources management. In this study, the streamflow response to climate change was investigated in the Lake Dianchi watershed, which has one of the most important eutrophic lakes in China. Daily time-series of temperature and precipitation in the future periods (2020s, 2050s and 2080s) were projected from HadCM3 model. Statistical Downscaling Model (SDSM) and the previously calibrated and validated Soil and Water Assessment Tool (SWAT) model were used to quantify the impacts of climate change on streamflow in this watershed. The results showed that SDSM can well capture the statistical relationships between the large scale climate variables and the observed weather at regional scale. The downscaled results showed that annual average maximum and minimum temperature would rise by 4.28℃ (3.25℃) and 4.71℃ (3.33℃) in the 2080s under A2 (B2) scenario. Annual average precipitation would decrease within the range between 20.34 mm to 74.12 mm under both scenarios in the future. Based on SWAT model simulation, annual average streamflow would decrease in the future by the declination of -7.12% to -21.83% and -6.34% to -17.09% under A2 (B2) scenarios in the outlet of this watershed. The frequency of drought and extreme rainfall events would increase in the future, which is not beneficial to protect Lake Dianchi. This study could lead to a better understanding of the streamflow response under climate change and also raised concerns about the sustainability of future water resources in Lake Dianchi watershed.

Keywords: Climate Change; Streamflow; Statistical Downscaling Model; SWAT; Lake Dianchi Watershed